Performance-Based Remediation in Composable Infrastructure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Computing devices face performance issues due to inefficient management of resources for data generation, storage, and transfer, leading to suboptimal utilization and compliance with performance and compliance standards.
Innovation Solution
A method and system for managing workloads on resource devices, involving workload generation, resource allocation, latency management, performance monitoring, and remediation, as well as ensuring security and data compliance through snapshot analysis, remediation, and certificate storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If continuous performance monitoring and analysis is performed on resource devices, then performance issues can be detected and remediated, but system complexity and computational overhead increase
Solution Approach 1:
The system performs preliminary actions by taking snapshots of performance metrics at scheduled intervals and storing them in a database before performance analysis is needed. This allows the system to have historical data ready for analysis without continuously processing live data, reducing real-time computational complexity while maintaining reliable performance monitoring.
Solution Approach 2:
The performance monitoring system is segmented into distinct components: snapshot acquisition, data storage, performance analysis, and remediation. The snapshot data is divided into individual metric records stored in a database, allowing selective analysis of specific metrics or time periods rather than processing all data continuously, thus reducing system complexity.
2Measurement precision
If multiple snapshots of performance metrics are collected and analyzed, then accurate performance assessment is achieved, but data storage requirements and processing time increase
Solution Approach 1:
Performance snapshots are collected and stored in advance in a database structure that organizes data by metric type, time stamps, and resource device identifiers. This preliminary organization allows the performance analysis function to quickly retrieve and process only the relevant snapshots needed for assessment, rather than searching through all collected data, thus maintaining measurement precision while reducing processing time.
3Reliability
If resource device remediation is performed automatically based on performance analysis, then performance compliance is maintained, but automation complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring performance metrics, comparing them against compliance standards, and automatically triggering remediation actions when violations are detected. The remediation actions are fed back into the system to correct performance issues, creating a closed-loop control mechanism that maintains performance compliance through measured automation rather than complex autonomous decision-making.
Data Source
AI summary
A method for managing data includes selecting a first workload, wherein the first workload is implemented on at least a resource device, obtaining a snapshot of performance metrics for the resource device, storing the snapshot of performance metrics in a performance database, making a first determination that a minimum number of previous snapshots have been obtained after a previous performance analysis, and in response to the first determination: performing a performance analysis on a set of previous snapshots of the first workload to obtain a performance report, making a second determination, based on the performance report, that the resource device does not meet standard performance, and in response to the second determination, performing a resource device remediation on the resource device.